Evolving multi-valued regulatory networks on tuneable fitness landscapes (2023)
Journal Article
Bull, L. (in press). Evolving multi-valued regulatory networks on tuneable fitness landscapes. Complex Systems -Champaign-,

Random Boolean networks have been used widely to explore aspects of gene regulatory networks. As the name implies, traditionally the model has used a binary representation scheme. This paper uses a modified form of the model through which to systemat... Read More about Evolving multi-valued regulatory networks on tuneable fitness landscapes.

A generalised dropout mechanism for distributed systems (2022)
Journal Article
Bull, L., & Liu, H. (in press). A generalised dropout mechanism for distributed systems. Artificial Life, https://doi.org/10.1162/artl_a_00393

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global con... Read More about A generalised dropout mechanism for distributed systems.

A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments (2022)
Book Chapter
Tsompanas, M., Bull, L., Adamatzky, A., & Balaz, I. (2022). A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments. In I. Balaz, & A. Adamatzky (Eds.), Cancer, Complexity, Computation (237-251). Springer. https://doi.org/10.1007/978-3-031-04379-6_10

This paper uses a recent explanation for the fundamental haploid-diploid lifecycle of eukaryotic organisms to present a new evolutionary algorithm that differs from all previous known work using diploid representations. A form of the Baldwin effect h... Read More about A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments.

Nonbinary representations in the NK and NKCS models (2022)
Journal Article
Bull, L. (2022). Nonbinary representations in the NK and NKCS models. Complex Systems -Champaign-, 31(1), 87-101. https://doi.org/10.25088/ComplexSystems.31.1.87

The NK model has been used widely to explore aspects of natural evolution and complex systems. Traditionally, the model has used a binary representation scheme. This paper introduces a modified form of the NK model through which to systematically exp... Read More about Nonbinary representations in the NK and NKCS models.

Evolving Boolean regulatory networks with variable gene expression times (2021)
Book Chapter
Bull, L. (2021). Evolving Boolean regulatory networks with variable gene expression times. In Handbook of Unconventional Computing (247-259). World Scientific Publishing. https://doi.org/10.1142/9789811235726_0007

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uni... Read More about Evolving Boolean regulatory networks with variable gene expression times.

Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types (2021)
Journal Article
Tsompanas, M. A., Bull, L., Adamatzky, A., & Balaz, I. (2021). Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types. IEEE Computational Intelligence Magazine, 16(4), 85-99. https://doi.org/10.1109/MCI.2021.3108306

There is a rich history of evolutionary algorithms tackling optimization problems where the most appropriate size of solutions, namely the genome length, is unclear a priori. Here, we investigated the applicability of this methodology on the problem... Read More about Evolutionary algorithms designing nanoparticle cancer treatments with multiple particle types.

On coevolution: Asymmetry in the NKCS model (2021)
Journal Article
Bull, L. (2021). On coevolution: Asymmetry in the NKCS model. BioSystems, 207, Article 104469. https://doi.org/10.1016/j.biosystems.2021.104469

The NKCS model was introduced to explore coevolutionary systems, that is, systems in which multiple species are closely interconnected. The fitness landscapes of the species are coupled to a controllable amount, where the underlying properties of the... Read More about On coevolution: Asymmetry in the NKCS model.

On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution (2021)
Journal Article
Bull, L. (2021). On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution. Artificial Life, 27(1), 15-25. https://doi.org/10.1162/artl_a_00335

Sexual selection is a fundamental aspect of evolution for all eukaryotic organisms with mating types. This article suggests intersexual selection is best viewed as a mechanism with which to compensate for the unavoidable dynamics of coevolution betwe... Read More about On the emergence of intersexual selection: Arbitrary trait preference improves female-male coevolution.

Autoencoding with a classifier system (2021)
Journal Article
Preen, R. J., Wilson, S. W., & Bull, L. (2021). Autoencoding with a classifier system. IEEE Transactions on Evolutionary Computation, 25(6), 1079 - 1090. https://doi.org/10.1109/TEVC.2021.3079320

Autoencoders are data-specific compression algorithms learned automatically from examples. The predominant approach has been to construct single large global models that cover the domain. However, training and evaluating models of increasing size com... Read More about Autoencoding with a classifier system.

Are artificial dendrites useful in neuro-evolution? (2021)
Journal Article
Bull, L. (2022). Are artificial dendrites useful in neuro-evolution?. Artificial Life, 27(2), 75-79. https://doi.org/10.1162/artl_a_00338

The significant role of dendritic processing within neuronal networks has become increasingly clear. This letter explores the effects of including a simple dendrite-inspired mechanism into neuro-evolution. The phenomenon of separate dendrite activati... Read More about Are artificial dendrites useful in neuro-evolution?.